Insider threats: the major challenge to security risk management

Security risk management is by definition, a subjective and complex exercise and it takes time to perform properly. Human resources are fundamental assets for any organization, and as any other asset, they have inherent vulnerabilities that need to be handled, i.e. managed and assessed. However, the nature that characterize the human behavior and the organizational environment where they develop their work turn these task extremely difficult, hard to accomplish and prone to errors. Assuming security as a cost, organizations are usually focused on the efficiency of the security mechanisms implemented that enable them to protect against external attacks, disregarding the insider risks, which are much more difficult to assess. All these demands an interdisciplinary approach in order to combine technical solutions with psychology approaches in order to understand the organizational staff and detect any changes in their behaviors and characteristics. This paper intends to discuss some methodological challenges to evaluate the insider threats and its impacts, and integrate them in a security risk framework, that was defined according to the security standard ISO/IEC_JTC1, to support the security risk management process.

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Towards effective control of P2P traffic aggregates in network infrastructures

Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

Sistema de apoio a rondas de segurança

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)

Os contornos das políticas sociais de apoio alimentar no Concelho de Braga

Dissertação de mestrado em Estudos da Criança (área de especialização em Intervenção Psicossocial com Crianças, Jovens e Famílias)

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.